Targeted change detection in remote sensing images

TL;DR

This paper introduces a formal problem statement and a new deep learning framework for targeted change detection in remote sensing images, enabling effective analysis of time series for specific object changes with practical business applications.

Contribution

It presents a formal problem formulation and a novel deep learning framework tailored for targeted change detection in satellite imagery.

Findings

Demonstrated the framework on real-world cases

Showed effectiveness in detecting specific changes over time

Highlighted potential business applications

Abstract

Recent developments in the remote sensing systems and image processing made it possible to propose a new method of the object classification and detection of the specific changes in the series of satellite Earth images (so called targeted change detection). In this paper we propose a formal problem statement that allows to use effectively the deep learning approach to analyze time-dependent series of remote sensing images. We also introduce a new framework for the development of deep learning models for targeted change detection and demonstrate some cases of business applications it can be used for.